AI assists in design of corrosion-resistant alloys
Name
43577_2023_633_ReferencePDF.pdf
Size
749.22 KB
Format
Adobe PDF
Checksum (MD5)
1aabb0f268ca50eb802257bbdb856917
Author(s)
Venugopal, Vineeth
Date Issued
December 6, 2023
Journal
MRS Bulletin
Publisher
Springer International Publishing
Citation
Venugopal, Vineeth. 2023. "AI assists in design of corrosion-resistant alloys." MRS Bulletin, 48.
Version
Author's final manuscript
Abstract
Alloy design can potentially benefit from artificial intelligence (AI). Within the broader context of advanced materials design, researchers have explored the creation of various alloys, including ferrous, high-entropy materials, and nonferrous metallic compositions, employing data-driven methodologies. However, a significant hurdle in these endeavors has been the scarcity of extensive, machine-readable databases suitable for training AI models. To address this challenge, researchers have turned to text mining and autonomous data extraction from literature sources. However, a major challenge with this approach is that the essential materials properties and features are not necessarily known, and must be obtained from textual sources to enhance the predictive accuracy of these models.
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1557/s43577-023-00633-1
